1. Field of the Invention
The present invention relates generally to unresolved target detection using an infrared focal plane array (IR FPA), and it more particularly relates to the detection of closely spaced multiple targets using a regional window as a discriminant function.
2. Description of the Related Art
In general, most current military sensors use single target detection and tracking approach. However, in many battlefield scenarios targets show up as closely-spaced pairs or groups. For example as shown in FIG. 1, air fighters 1 almost always come as a pair that includes a leading fighter and an accompanying fighter. Frequently, ballistic missiles 2 are launched in pairs or groups located in a closely-spaced area. Navy warships 3 usually move as a fleet (ship group), and army trucks and tanks 4 on a large scale battlefield move and show up in teams and groups, as shown in FIG. 1. Therefore, the capability to detect and track CSOs (Closely Spaced Objects) is critical for military sensing.
The traditional approach for CSO detection, uses a nonlinear Least Square (Levenberg-Marquardt) algorithm to detect CSOs. A prior art technique that utilizes the Levenberg-Marquardt algorithm is described in an article by Svetlana G. Shasharina and John Cary, “An Improved Levenberg-Marquardt Solver for Multiple-Target Optimization,” Bull. Am. Phys. Soc. 44 (7), 82 (1999). The traditional approach for CSO detection is more of a scientific approach, and it has problems in real world applications. For example, the traditional approach needs initial guesses of target numbers, and it does not deal well with target phasing problems. Moreover, it is not guaranteed to always find the global minimum, and it requires heavy computations for large iterations that do not always converge.
Accordingly, a simpler and more reliable engineering approach for detecting CSO's is needed.